2016 Summer Specialist Meeting

Human Dynamics and Big Data
Hosted by the Center for Human Dynamics in the Mobile Age (HDMA)

NSF-IBSS Project
August 01-02, 2016 in San Diego, California, USA

This specialist meeting (workshop) is funded by the National Science Foundation (NSF) project award #1416509, IBSS: Spatiotemporal Modeling of Human Dynamics Across Social Media and Social Networks. The goal of this workshop is to foster the multidisciplinary collaboration in related research disciplines, including geography, linguistics, computer science, political science, public health, and communication. The two-day workshop (August 01 and August 02, 2016), organized by the Center for Human Dynamics in the Mobile Age (HDMA) at San Diego State University, will bring together over 30 specialists drawn from many disciplines. The workshop will assess the current state of the art technologies and tools for studying human dynamics and Big Data, identify and prioritize a research agenda, and begin the development of a research community of collaborating scholars working on these Big Data, social media, and human dynamics issues.

Over 30 specialists and scholars will be invited by the NSF IBSS project team, consisting of PI Ming-Hsiang Tsou (Geography) and Co-PIs from Brian Spitzberg (Communication), Jean Mark Gawron (Linguistics), Heather Corliss (Public Health), Jay Lee (Geography, Kent State), Xinyue Ye (Geography, Kent State), and Xuan Shi (Geosciences, U of Arkansas). The meeting will include plenary presentations by invited experts, lightning talks, and focus group discussions. This workshop will generate a final report to be published on the IBSS project website. This year, our research theme will be “Human Dynamics and Big Data”. The dynamic supply of big data from millions of social media messages, GPS tracks, medical records, wireless sensors, electronic health records, web pages, and cellular phones, becomes an important research domain. Big data provide untapped potentials for discovering and analyzing dynamic human problems, including business analytics, disease outbreaks, traffic patterns, urban dynamics, bioinformatics, and environmental changes. Such data offer golden opportunities for scientists to develop new tools, new methods, and new theories for human dynamics. However, Big Data Science requires transdisciplinary collaboration and research methodologies to integrate multiple perspectives into collaborative research endeavors. This workshop will build a collaborative platform for scientists and researchers to work together. Specific research questions to be addressed in the workshop may include:

1. How to reduce the dimensionality of big data datasets in ways that help humans conduct analysis or create knowledge?
2. How do different social network structures affect the scope and speed of the spatial diffusion processes for memes?
3. Are there community detection approaches to social media that can fruitfully provide metrics/ratios of pro- versus counter-frame social networks predictive of social policy formation (e.g., vaccine policy, marijuana legalization, etc.)?
4. Will adapting the Multilevel Model of Meme Diffusion to include behavioral theories result in a model that improves prediction of meme diffusion?
5. Are there search filters/ontologies that can facilitate focus on actionable social media messages during natural disasters?
6. How can parallel and distributed computing resources facilitate big data analytics on human dynamics?
7. What are opportunities and challenges of open source toolkit development for human dynamics studies?

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Spatiotemporal Modeling of Human Dynamics Across Social Media and Social Networks is funded by National Science Foundation, Division of Computer and Network Systems, NSF IBSS Award Abstract #1416509. Opinions expressed are those of the authors and not necessarily those of the National Science Foundation. NSF Award Information